Chinese character recognition : studies of complexity effect on recognition efficiency, spatial frequency characteristics, crowding and expertise

2013 ◽  
Author(s):  
On-ting Lo
2020 ◽  
Vol 4 (4) ◽  
pp. 271-279
Author(s):  
Rui Guo

The intelligent recognition tool for bronze inscriptions of the Shang and Zhou dynasties—the “Shang Zhou Bronze Inscriptions Intelligent Mirror”—was successfully invented in Shanghai. This mirror, based on the computer technology of artificial intelligence (AI) image recognition and image retrieval, succeeds in automagical recognition of bronze inscriptions, both single letters and full texts. This research leads the trend of the AI recognition of Ancient Chinese characters and accumulates valuable experience for the development of inter-disciplinary research on Chinese character recognition. This essay emphasizes the importance of the bronze inscriptions of the Shang and Zhou dynasty database in the AI recognition of bronze inscriptions, introduces the functional components of this tool, and shares the whole research process in order to offer experience for the related research on AI recognition of other types of Ancient Chinese characters as well as ideographs in the world scope. “Shang Zhou Bronze Inscriptions Intelligent Mirror” as a tool for bronze inscription recognition also has room for improvement and support, and guidance from experts in similar areas is greatly welcomed.


2013 ◽  
Vol 760-762 ◽  
pp. 1452-1456
Author(s):  
Chao Zheng ◽  
Hua Yang ◽  
Xing Yang ◽  
Chao Chao Huang ◽  
Xiao Di Wu

Low-resolution Chinese character recognition of license plate is always a difficult problem. For solving it, we must think about the distinctiveness of character feature and the counting speed of method simultaneously. In this paper, we proposed a simple and effective feature extraction algorithm. First, extract the statistical feature of Chinese character based on decomposing stroke with wavelet transform. Second, apply Elastic Mesh Algorithm into extracting wavelet coefficient of decomposing stroke to get the structure information of Chinese character. The experimental results show the method is robust against low quality Chinese characters, such as skew, fuzzy, glue, distorted character, and easy to be used in actual projects with simple advantage.


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